With the proliferation of vast amount of information on the Internet, it is often very difficult to search and locate relevant information without having to first expend a great deal time to peruse over many irrelevant search results. Depending on the material that is being sought, the user is often frustrated by having to view many immaterial search results.
Scoring or ranking is one of the core problems in search, for example, especially in shopping/product search. If a search cannot provide the most relevant documents near the top of a listing of search results, it is often called irrelevant. Users tend to have higher relevancy requirements on searches such as shopping/product search than regular web searches because their goals are not just in finding one relevant result. They often want to see the most relevant products and be able to compare among different products and different merchants.
Pure text relevance based scoring is the foundation of several search technologies. The basic idea is to find text that matches in the document's title, description, and other fields. Additional refinements can be added, e.g., providing some fields, like title, with a higher weight, providing phrase matches with a higher weight and so on. However, all these pure text relevancy scoring approaches have a problem in generating the most relevant search results because they cannot determine what exactly the users are searching for.
For example, in a pure text relevancy search, when searching for the term “computer”, documents with title like “Sony VAIO FX340” would not be viewed as a good text match because the title does not contain the term “computer”, whereas documents with titles like “computer case” will be viewed as a good match. This example demonstrates that a search for a computer will likely produce search results with many irrelevant items.
Even when all the results are perceived to be relevant, it would still be preferable to provide products that are more popular with a higher score or rank. However, a pure text relevancy search would not be able to provide this important distinction.
Therefore, there is a need in the art for a method and apparatus that provides search results with higher relevancy.